Profile Adjustment Apparatus Optimizing Color Reproduction Accuracy
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Solution Overview
Problem
Existing color management systems face challenges in achieving high color reproduction accuracy due to errors in ICC profiles, particularly when converting between device-dependent and device-independent color spaces, leading to discrepancies in color reproduction across different printing devices.
Innovation Solution
A profile adjustment method that utilizes a computer-based process to optimize the correspondence between CMYK values in a device-dependent color space and Lab values in a profile connection space, employing optimization techniques such as quasi-Newton methods and conjugate gradient methods to minimize color differences and ensure accurate color conversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an A2B table of the output profile is used to convert CMYK p values into Lab values, then color conversion can be performed, but an error in the A2B table causes a difference between the Lab value and the actual target Lab value, leading to inaccurate color reproduction
Solution Approach 1:
The patent implements feedback by using the optimized Lab values (derived from B2A conversion and target color comparison) to adjust and refine the A2B table in the output profile. This closed-loop approach allows the system to learn from conversion errors and progressively improve accuracy, resolving the contradiction between being able to perform conversion and ensuring high accuracy.
Solution Approach 2:
The patent changes the parameters of the A2B table by optimizing Lab values through iterative adjustment. The system modifies the correspondence relationships in the profile based on optimization results from multiple conversions, thereby improving the accuracy parameter while maintaining the functional capability of the conversion table.
2Measurement precision
If spot color adjustment is performed by modifying the ICC profile, then color accuracy can be improved, but extensive recalibration and adjustment time is required
Solution Approach 1:
The patent performs preliminary optimization of Lab values using automated algorithms (quasi-Newton method, conjugate gradient method) before actual printing. This preliminary computational adjustment reduces the need for extensive manual recalibration and spot color tweaking, significantly cutting down adjustment time while maintaining high color accuracy.
Solution Approach 2:
The patent replaces manual mechanical adjustment processes with automated computational optimization. Instead of relying on manual spot color adjustment and iterative printing tests, the system uses mathematical optimization algorithms to automatically refine profile parameters, reducing both time and human effort.
3Ease of manufacture
If the input profile is adjusted based on erroneous Lab values from the A2B table, then profile modification can be made, but the expected color fails to be acquired due to the underlying error
Solution Approach 1:
The patent introduces an intermediary optimization process that uses the B2A table (which is assumed to be accurate) as a mediator. Instead of directly adjusting the input profile based on potentially erroneous A2B conversions, the system uses the reverse B2A conversion to derive target Lab values, which then serve as the basis for accurate input profile adjustment.
Solution Approach 2:
The patent inverts the conventional adjustment approach by using B2A conversion (output profile) to inform A2B adjustment (input profile). Instead of converting input to output and adjusting based on that, the system converts output back to Lab space and uses those values to guide input profile optimization, effectively working backwards to achieve better accuracy.
Data Source
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AI summary
In an output profile representing a correspondence relationship between device independent coordinate values and second coordinate values in a second device dependent color space, a color conversion table used to convert the device independent coordinate values into the second coordinate values is defined as a first conversion table, and the device independent coordinate values at the adjustment point are defined as to-be-adjusted PCS values. In optimization, an optimization process including an element making provisional color values closer to an adjustment target is executed, the provisional color value being acquired by a conversion, in accordance with the first conversion table, of provisional PCS values resulting from a change in the to-be-adjusted PCS values, thus acquiring an optimal solution for the device independent coordinate values corresponding to the adjustment target.